Evaluation Of Potential Changes In The Tax Treatment Of Company Cars In Canada
Bibliographic record
Abstract
Abstract Canada has ratified the Kyoto Protocol to the United Nations Framework Convention on Climate Change, which commits it to reducing average annual greenhouse gas (GHG) emissions between 2008 and 2012 to 6 per cent below the 1990 level. Because of increases in population, economic growth, and certain industrial activities, GHG emissions in Canada had grown to 24 per cent above 1990 levels by 2003, and are forecast to continue growing through to 2012 in the absence of strong policies.2 Canada’s commitment under the Kyoto Protocol therefore represents a reduction of GHG emissions of more than 30 per cent from business as usual levels. Over the past fifteen years, the Government of Canada has developed a series of plans to try to meet this commitment, though the current government has recently abandoned this objective. In The Budget Plan 2005, the Government of Canada outlines the importance of economic instruments, such as grants, subsidies, and tax measures, in meeting economic and environmental goals simultaneously. In particular, the government discusses the potential for using the tax system to pursue broader objectives (additional to its basic role of generating revenue). One related objective that the government may decide to continue to pursue is the correction of negative environmental externalities, which occur when an individual or company does not pay the full cost of polluting. In this situation, market prices understate actual costs to society, and the individual or company produces more pollution than is socially optimal, resulting in a market failure. Under certain conditions, government may be able to correct for such market failures by using economic instruments to establish improved price signals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".